就线性定常/时变系统以及非线性系统, 依据特征模型理论, 给出动态系统的一阶特征模型. 其特征参数随时间变化, 即以一阶时变差分方程描述受控系统的动态特性;
与二阶和三阶特征模型相比较, 一阶模型具更少参数.为解决由一阶特征模型描述的系统的控制问题, 提出基于遗忘因子迭代学习辨识的自适应迭代学习控制方法.
迭代学习辨识适于时变参数的估计, 它允许被估计参数随时间快速变化, 抑或突变.以直线伺服系统的位置跟踪控制为例,  给出一种基于特征模型与LQ最优控制策略的自适应迭代学习控制方案.仿真与实验结果表明, 提出的控制方案能够有效实现受控系统的位置跟踪控制.

This paper presents the first-order time-varying difference equation, the characteristic odel. Only two parameters are involved in the equation. The adaptive iterative earning control method is suggested to deal with the characteristic-model based control problem, here the learning identification algorithms with a forgetting factor are introduced to stimate the time-varying unknowns. For PMLSM servo-systems, in this paper, an adaptive terative learning control scheme is proposed based on the LQ optimal control strategy. Numerical nd expereiment results are presented to demonstrate effectiveness of the control scheme.